Position Overview

We are seeking an experienced Validation Lead – Autonomous Driving & ADAS to lead the end-to-end verification and validation (V&V;) of our autonomous driving systems, from component-level testing to integrated vehicle validation. The ideal candidate will bring strong technical expertise in ADAS and autonomous driving validation, simulation environments, embedded automotive systems, and safety-critical software testing.

This is a hands-on technical leadership role responsible for defining validation strategies, building scalable testing frameworks, leading validation teams, and ensuring that RoshAi's autonomy solutions meet performance, reliability, safety, and production-readiness requirements.

The role involves close collaboration with autonomy architects, perception, planning, control, hardware, functional safety, and vehicle integration teams to deliver robust Level 2+ to Level 4 autonomous driving capabilities.

Key Responsibilities

1. Validation Strategy & Technical Leadership

- Define and own the end-to-end verification and validation strategy for ADAS and autonomous driving systems, including Level 2+ to Level 4 functions.
- Develop comprehensive validation plans covering perception, sensor fusion, localization, prediction, planning, control, and vehicle interfaces.
- Establish validation methodologies, acceptance criteria, performance benchmarks, and quality gates aligned with system requirements and Operational Design Domain (ODD).
- Lead validation activities throughout the product development lifecycle, from initial development to vehicle deployment.
- Drive test automation, continuous validation, and improvements in testing efficiency and coverage.

2. Simulation, MiL, SiL & HiL Validation

- Lead the design, development, and execution of validation frameworks across:

-Model-in-the-Loop (MiL) -Software-in-the-Loop (SiL)

-Hardware-in-the-Loop (HiL)

-Vehicle-in-the-Loop (ViL)

-Real-world vehicle testing

- Develop and execute scenario-based testing using simulation platforms such as CARLA, IPG CarMaker, dSPACE, NVIDIA DRIVE Sim, or equivalent tools.
- Define test scenarios covering normal operations, edge cases, sensor failures, environmental variations, and safety-critical situations.
- Establish automated regression testing frameworks integrated with CI/CD pipelines.
- Ensure consistency and traceability between simulation results and real-world vehicle performance.

3. Autonomous Driving System Validation

- Lead system-level and subsystem-level validation of the autonomy stack, including:

-Perception: Object detection, classification, tracking, and environmental understanding. -Sensor Fusion: Camera, LiDAR, Radar, and multi-sensor integration.

-Localization: Positioning accuracy, mapping, and localization robustness.

-Prediction & Planning: Behaviour prediction, decision-making, path planning, and trajectory generation.

-Control: Lateral and longitudinal control, vehicle dynamics, and trajectory tracking.

-Vehicle Integration: Drive-by-wire, braking, steering, throttle, and communication interfaces.

- Define measurable KPIs for functional performance, latency, reliability, robustness, and system safety.
- Identify performance limitations, integration defects, and critical failure modes through structured validation.

4. Vehicle Testing & Field Validation





- Plan and lead validation activities on prototype vehicles, test tracks, proving grounds, and controlled operational environments.
- Develop test procedures for autonomous driving functions, including obstacle avoidance, emergency braking, lane keeping, automated navigation, and fallback operations.
- Validate vehicle behaviour across different road conditions, traffic scenarios, environmental conditions, and operational constraints.
- Coordinate with vehicle integration, hardware, and deployment teams for test readiness and execution.
- Lead issue investigation, root-cause analysis, defect tracking, and closure of validation findings.
- Establish effective processes for test data collection, log analysis, scenario replay, and field performance evaluation.

5. Functional Safety, Compliance & Quality

- Ensure validation processes align with applicable automotive standards and engineering practices, including:
- ISO 26262 – Functional Safety
- ISO 21448 – Safety of the Intended Functionality (SOTIF)
- ISO/SAE 21434 – Automotive Cybersecurity
- Automotive SPICE (ASPICE)
- Develop safety-related validation scenarios covering fault injection, system degradation, fallback strategies, and minimal-risk conditions.
- Maintain requirements traceability, test coverage, validation reports, and supporting evidence for safety assessments.
- Collaborate with functional safety and system architecture teams to support safety cases and design reviews.
- Drive compliance with internal engineering quality standards and customer validation requirements.

6. Test Automation, Tools & Data Analytics

- Design and improve automated testing frameworks for autonomy software and embedded automotive systems.
- Develop Python/C++-based test scripts, validation utilities, and automated reporting tools.
- Establish data-driven validation processes using vehicle logs, simulation outputs, and test results.
- Define dashboards and metrics to monitor test coverage, defect trends, regression performance, and release readiness.
- Support integration of validation workflows with CI/CD, cloud-based simulation, and large-scale data processing environments.

7. Team Leadership & Cross-Functional Collaboration

- Lead, mentor, and develop validation engineers and test automation specialists.
- Allocate validation activities, establish priorities, and ensure timely execution against project milestones.
- Collaborate closely with autonomy architects, software development teams, hardware engineers, and technical program managers.
- Participate in technical design reviews to ensure system requirements are measurable, testable, and verifiable.
- Communicate validation progress, technical risks, defect severity, and release-readiness assessments to engineering leadership.
- Drive a culture of engineering quality, technical accountability, and continuous improvement.

Required Skills & Experience

Technical Experience





- 10+ years of experience in automotive software validation, ADAS, autonomous driving, or safety-critical embedded systems, including at least 3 years in a technical lead or validation leadership role.
- Strong hands-on experience in system-level validation of ADAS or autonomous driving functions.
- Proven expertise in MiL, SiL, HiL, and vehicle-level testing methodologies.
- Strong understanding of autonomous driving architecture, including perception, sensor fusion, localization, planning, and control.
- Proficiency in Python and C++ for test automation, debugging, and validation framework development.
- Experience with ROS/ROS 2, embedded Linux, and automotive software integration.
- Strong knowledge of automotive communication protocols such as CAN, CAN-FD, Automotive Ethernet, and diagnostics.
- Experience validating embedded automotive ECUs, sensor interfaces, and drive-by-wire systems.
- Testing & Validation Expertise
- Hands-on experience with simulation and validation tools such as CARLA, IPG CarMaker, dSPACE, Vector CANoe/CANalyzer, MATLAB/Simulink, or NVIDIA DRIVE Sim.
- Experience developing automated test frameworks and scenario-based validation environments.
- Strong knowledge of requirements-based testing, test design, coverage analysis, defect management, and traceability.
- Experience with performance analysis, vehicle log analysis, fault injection, and root-cause investigation.
- Familiarity with Git, Jenkins, CI/CD pipelines, and software quality assurance practices.

Leadership & Delivery

- Demonstrated experience leading validation teams and managing complex automotive testing programmes.
- Ability to translate system requirements into validation plans, test strategies, and measurable acceptance criteria.
- Strong analytical and problem-solving skills, with the ability to troubleshoot complex system-level issues.
- Excellent communication, technical documentation, stakeholder management, and cross-functional coordination skills.
- Experience managing validation deliverables, technical risks, and release-readiness reviews.
- Preferred Qualifications
- Experience in Level 3/Level 4 autonomous driving development and validation programmes.
- Exposure to autonomous vehicle retrofit solutions, industrial autonomous vehicles, or off-highway autonomy applications.
- Experience with ODD-based validation, scenario coverage analysis, and safety-critical edge-case testing.
- Knowledge of ISO 26262, SOTIF, ASPICE, and automotive cybersecurity requirements.
- Experience with NVIDIA Jetson/DRIVE platforms or other automotive compute platforms.
- Familiarity with cloud-based simulation, large-scale test automation, and data analytics.
- Experience working with automotive OEMs, Tier-1 suppliers, autonomous mobility companies, or robotics organisations.

What We Expect

We are looking for a technically robust validation leader who goes beyond executing test cases and takes complete ownership of validation strategy, system quality, and release readiness.

The successful candidate should be capable of building validation frameworks from the ground up, challenging system assumptions, identifying critical failure scenarios, and working closely with engineering teams to ensure that autonomous driving solutions perform safely and reliably in real-world environments.

📌 Validation Lead (Kochi)
🏢 RoshAi
📍 Kochi